Plot categorical heatmaps with seaborn
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Updated
Aug 30, 2022 - Python
Plot categorical heatmaps with seaborn
Perform a chi-square independence test.
Keras, Tensorflow eager execution implementation of Categorical Variational Autoencoder
A python package for plotting Evidence Gap Maps using Plotly
A simple preprocessing method for Machine Learning
Quasi-determinism screening for fast Bayesian Network Structure Learning (from T.Rahier's PhD thesis, 2018)
Associated to SAMO paper
WF16 federation gateway for mo:os kernels — URN-prefix shard routing. Go, stdlib-first.
Jupyter notebooks on custom loss functions in TensorFlow/Keras: modified MSE penalizing overconfidence and Categorical Focal Loss with L1/L2 regularization for imbalanced multi-class tasks (e.g., cats_vs_dogs). Includes model building, preprocessing, GPU checks, and focuses on learning mechanics over metrics.
Categorical hypergraph rewriting kernel — semantic functorial network over distributed compute. Go, stdlib-first.
Visualize gender-based employment status and recruitment sources using stacked bar plots in Python.
ML project template created while following the Abhishek Thakur's youtube video
Data on Youtube trending videos , cleaning and EDA
Extensions and additions to vcd: Visualizing Categorical Data
Fun Project -: Playing with the statistics. Main Motto -: Trying to understand the statistics underneath the various most commonly used Machine Learning Models. I have used two library i.e. Stats-Model and Scikit-Learn.
EDA / Data Visualization of Hotstar Shows
The following codes were used to conduct Confirmatory Factor Analysis and Structural Equation Modeling in R, and Multiple Group Analysis in R for my thesis entitled "Analysing DASS through Structural Equation Modeling". Note: THE DATA USED IS NOT MY OWN AND WAS OBTAINED FROM Open-Source Psychometrics Project (https://fhssrsc.byu.edu/r-works)
Sufficient Representation for Categorical Variables https://arxiv.org/abs/1908.09874v1
Titanic Survival Prediction Using Decision Tree. This project uses a Decision Tree Classifier to predict Titanic passenger survival based on the Kaggle dataset. It covers data preprocessing, feature engineering, and model training with Scikit-learn.
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